Posted:1 week ago|
Platform:
On-site
Full Time
Built systems that power B2B SaaS products? Want to scale them for real-world impact? Our client is solving some of the toughest data problems in India powering fintech intelligence, risk engines, and decision-making platforms where structured data is often missing. Their systems are used by leading institutions to make sense of complex, high-velocity datasets in real time. We’re looking for a Senior Data Engineer who has helped scale B2B SaaS platforms, built pipelines from scratch, and wants to take complete ownership of data architecture and infrastructure decisions. What You'll Do: Design, build, and maintain scalable ETL pipelines using Python , PySpark , and Airflow Architect ingestion and transformation workflows using AWS services like S3 , Lambda , Glue , and EMR Handle large volumes of structured and unstructured data with a focus on performance and reliability Lead data warehouse and schema design across Postgres , MongoDB , DynamoDB , and Elasticsearch Collaborate cross-functionally to ensure data infrastructure aligns with product and analytics goals Build systems from the ground up and contribute to key architectural decisions Mentor junior team members and guide implementation best practices You’re a Great Fit If You Have: 3 to 7 years of experience in data engineering , preferably within B2B SaaS/AI environments ( mandatory ) Strong programming skills in Python and experience with PySpark , and Airflow Strong expertise in designing, building and deploying data pipelines in product environments Mandatory experience in NoSQL databases Hands-on with AWS data services and distributed data processing tools like Spark or Dask Understanding of data modeling , performance tuning , and database design Experience working in fast-paced, product-driven teams and have seen the 0 to 1 journey Awareness of async programming and how it applies in real-world risk/fraud use cases Experience mentoring or guiding junior engineers is preferred Role Details: Location: Mumbai (On-site WFO) Experience: 3 to 7 years Budget: 20 to 30 LPA (Max) Notice Period: 30 days or less If you're from a B2B SaaS background and looking to solve meaningful, large-scale data problems we’d love to talk. Apply now or reach out directly to learn more. Show more Show less
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